{
  "cells": [
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "3hWMQQOdJMbx"
      },
      "source": [
        "# RAG Pipeline With Gemma 2, MongoDB and Hugging Face [Open Models]\n",
        "\n",
        "[![Open In Colab](https://colab.research.google.com/assets/colab-badge.svg)](https://colab.research.google.com/github/mongodb-developer/GenAI-Showcase/blob/main/notebooks/rag/rag_with_gemma2_mongodb_open_models.ipynb)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "_XtqPyEuJYjz"
      },
      "source": [
        "## Set Up Libraries"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 4,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "NoFjgZHHWlXp",
        "outputId": "629de58f-70fe-471b-fa1e-f8700fc8c0f9"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m547.8/547.8 kB\u001b[0m \u001b[31m7.2 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m13.0/13.0 MB\u001b[0m \u001b[31m41.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m1.2/1.2 MB\u001b[0m \u001b[31m53.9 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m227.1/227.1 kB\u001b[0m \u001b[31m28.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m40.8/40.8 MB\u001b[0m \u001b[31m40.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m116.3/116.3 kB\u001b[0m \u001b[31m17.4 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m64.9/64.9 kB\u001b[0m \u001b[31m9.7 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m194.1/194.1 kB\u001b[0m \u001b[31m25.1 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m134.8/134.8 kB\u001b[0m \u001b[31m20.0 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m307.7/307.7 kB\u001b[0m \u001b[31m36.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m21.3/21.3 MB\u001b[0m \u001b[31m70.5 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h\u001b[31mERROR: pip's dependency resolver does not currently take into account all the packages that are installed. This behaviour is the source of the following dependency conflicts.\n",
            "cudf-cu12 24.4.1 requires pandas<2.2.2dev0,>=2.0, but you have pandas 2.2.2 which is incompatible.\n",
            "cudf-cu12 24.4.1 requires pyarrow<15.0.0a0,>=14.0.1, but you have pyarrow 16.1.0 which is incompatible.\n",
            "google-colab 1.0.0 requires pandas==2.0.3, but you have pandas 2.2.2 which is incompatible.\n",
            "google-colab 1.0.0 requires requests==2.31.0, but you have requests 2.32.3 which is incompatible.\n",
            "ibis-framework 8.0.0 requires pyarrow<16,>=2, but you have pyarrow 16.1.0 which is incompatible.\u001b[0m\u001b[31m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m9.3/9.3 MB\u001b[0m \u001b[31m23.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[2K     \u001b[90m━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━━\u001b[0m \u001b[32m309.4/309.4 kB\u001b[0m \u001b[31m5.8 MB/s\u001b[0m eta \u001b[36m0:00:00\u001b[0m\n",
            "\u001b[?25h"
          ]
        }
      ],
      "source": [
        "!pip install --upgrade --quiet datasets pandas pymongo sentence_transformers\n",
        "!pip install --upgrade --quiet transformers\n",
        "# Install below if using GPU\n",
        "!pip install --upgrade --quiet accelerate"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "7myisb4nJgZa"
      },
      "source": [
        "## Data Loading"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 5,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 779,
          "referenced_widgets": [
            "e33f6b3a1247488890282df389b6ed61",
            "23e0098f59854da2a408d9f229fe482b",
            "b902ddfd9f52410cb70bd73c477683b4",
            "07c11c417b2041dcbff3c62bf9fd410b",
            "0ea6c486a6e3472396f51d25828f183b",
            "679d124f567e47f186f8b7d38037cf16",
            "b93d153824b243b68c48017f45db3139",
            "acdd038e8c7140e2af6a9084bbd42410",
            "91342c5ebe334efda4c002e3f7e5d2a3",
            "e5624cfc65d84f1cb193080dc1919758",
            "38cf7c5ca6e1476cb01e655c58d856a8"
          ]
        },
        "id": "LLUInmm_XVnZ",
        "outputId": "0b06d525-4ebd-490f-d92b-95e61cef9df9"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "e33f6b3a1247488890282df389b6ed61",
              "version_major": 2,
              "version_minor": 0
            },
            "text/plain": [
              "Downloading readme:   0%|          | 0.00/6.17k [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "      <td>https://m.media-amazon.com/images/M/MV5BMzgxOD...</td>\n",
              "      <td>[English]</td>\n",
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              "      <td>The Perils of Pauline</td>\n",
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              "      <td>0</td>\n",
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              "      <td>Michael \"Beau\" Geste leaves England in disgrac...</td>\n",
              "      <td>101.0</td>\n",
              "      <td>[Action, Adventure, Drama]</td>\n",
              "      <td>Michael \"Beau\" Geste leaves England in disgrac...</td>\n",
              "      <td>[Herbert Brenon]</td>\n",
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              "      <td>[USA]</td>\n",
              "      <td>None</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Ronald Colman, Neil Hamilton, Ralph Forbes, A...</td>\n",
              "      <td>Beau Geste</td>\n",
              "      <td>0</td>\n",
              "      <td>None</td>\n",
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              "      <th>3</th>\n",
              "      <td>Seeking revenge, an athletic young man joins t...</td>\n",
              "      <td>88.0</td>\n",
              "      <td>[Adventure, Action]</td>\n",
              "      <td>A nobleman vows to avenge the death of his fat...</td>\n",
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              "      <td>https://m.media-amazon.com/images/M/MV5BMzU0ND...</td>\n",
              "      <td>None</td>\n",
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              "      <td>The Black Pirate</td>\n",
              "      <td>1</td>\n",
              "      <td>None</td>\n",
              "      <td>{'id': 16654, 'rating': 7.2, 'votes': 1146}</td>\n",
              "      <td>{'nominations': 0, 'text': '1 win.', 'wins': 1}</td>\n",
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              "      <td>[-0.005927917, -0.033394486, 0.0015323418, -0....</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>An irresponsible young millionaire changes his...</td>\n",
              "      <td>58.0</td>\n",
              "      <td>[Action, Comedy, Romance]</td>\n",
              "      <td>The Uptown Boy, J. Harold Manners (Lloyd) is a...</td>\n",
              "      <td>[Sam Taylor]</td>\n",
              "      <td>[Ted Wilde (story), John Grey (story), Clyde B...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BMTcxMT...</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Harold Lloyd, Jobyna Ralston, Noah Young, Jim...</td>\n",
              "      <td>For Heaven's Sake</td>\n",
              "      <td>0</td>\n",
              "      <td>PASSED</td>\n",
              "      <td>{'id': 16895, 'rating': 7.6, 'votes': 918}</td>\n",
              "      <td>{'nominations': 1, 'text': '1 nomination.', 'w...</td>\n",
              "      <td>movie</td>\n",
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            "text/plain": [
              "                                                plot  runtime  \\\n",
              "0  Young Pauline is left a lot of money when her ...    199.0   \n",
              "1  A penniless young man tries to save an heiress...     22.0   \n",
              "2  Michael \"Beau\" Geste leaves England in disgrac...    101.0   \n",
              "3  Seeking revenge, an athletic young man joins t...     88.0   \n",
              "4  An irresponsible young millionaire changes his...     58.0   \n",
              "\n",
              "                       genres  \\\n",
              "0                    [Action]   \n",
              "1     [Comedy, Short, Action]   \n",
              "2  [Action, Adventure, Drama]   \n",
              "3         [Adventure, Action]   \n",
              "4   [Action, Comedy, Romance]   \n",
              "\n",
              "                                            fullplot  \\\n",
              "0  Young Pauline is left a lot of money when her ...   \n",
              "1  As a penniless man worries about how he will m...   \n",
              "2  Michael \"Beau\" Geste leaves England in disgrac...   \n",
              "3  A nobleman vows to avenge the death of his fat...   \n",
              "4  The Uptown Boy, J. Harold Manners (Lloyd) is a...   \n",
              "\n",
              "                              directors  \\\n",
              "0  [Louis J. Gasnier, Donald MacKenzie]   \n",
              "1       [Alfred J. Goulding, Hal Roach]   \n",
              "2                      [Herbert Brenon]   \n",
              "3                       [Albert Parker]   \n",
              "4                          [Sam Taylor]   \n",
              "\n",
              "                                             writers countries  \\\n",
              "0  [Charles W. Goddard (screenplay), Basil Dickey...     [USA]   \n",
              "1                             [H.M. Walker (titles)]     [USA]   \n",
              "2  [Herbert Brenon (adaptation), John Russell (ad...     [USA]   \n",
              "3  [Douglas Fairbanks (story), Jack Cunningham (a...     [USA]   \n",
              "4  [Ted Wilde (story), John Grey (story), Clyde B...     [USA]   \n",
              "\n",
              "                                              poster  languages  \\\n",
              "0  https://m.media-amazon.com/images/M/MV5BMzgxOD...  [English]   \n",
              "1  https://m.media-amazon.com/images/M/MV5BNzE1OW...  [English]   \n",
              "2                                               None  [English]   \n",
              "3  https://m.media-amazon.com/images/M/MV5BMzU0ND...       None   \n",
              "4  https://m.media-amazon.com/images/M/MV5BMTcxMT...  [English]   \n",
              "\n",
              "                                                cast                  title  \\\n",
              "0  [Pearl White, Crane Wilbur, Paul Panzer, Edwar...  The Perils of Pauline   \n",
              "1  [Harold Lloyd, Mildred Davis, 'Snub' Pollard, ...     From Hand to Mouth   \n",
              "2  [Ronald Colman, Neil Hamilton, Ralph Forbes, A...             Beau Geste   \n",
              "3  [Billie Dove, Tempe Pigott, Donald Crisp, Sam ...       The Black Pirate   \n",
              "4  [Harold Lloyd, Jobyna Ralston, Noah Young, Jim...      For Heaven's Sake   \n",
              "\n",
              "   num_mflix_comments   rated                                         imdb  \\\n",
              "0                   0    None    {'id': 4465, 'rating': 7.6, 'votes': 744}   \n",
              "1                   0    TV-G   {'id': 10146, 'rating': 7.0, 'votes': 639}   \n",
              "2                   0    None   {'id': 16634, 'rating': 6.9, 'votes': 222}   \n",
              "3                   1    None  {'id': 16654, 'rating': 7.2, 'votes': 1146}   \n",
              "4                   0  PASSED   {'id': 16895, 'rating': 7.6, 'votes': 918}   \n",
              "\n",
              "                                              awards   type  metacritic  \\\n",
              "0    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN   \n",
              "1  {'nominations': 1, 'text': '1 nomination.', 'w...  movie         NaN   \n",
              "2    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN   \n",
              "3    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN   \n",
              "4  {'nominations': 1, 'text': '1 nomination.', 'w...  movie         NaN   \n",
              "\n",
              "                                      plot_embedding  \n",
              "0  [0.0007293965299999999, -0.026834568000000003,...  \n",
              "1  [-0.022837115, -0.022941574000000003, 0.014937...  \n",
              "2  [0.00023330492999999998, -0.028511643000000003...  \n",
              "3  [-0.005927917, -0.033394486, 0.0015323418, -0....  \n",
              "4  [-0.0059373598, -0.026604708, -0.0070914757000...  "
            ]
          },
          "execution_count": 5,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Load Dataset\n",
        "import pandas as pd\n",
        "from datasets import load_dataset\n",
        "\n",
        "# Make sure you have an Hugging Face token(HF_TOKEN) in your development environemnt before running the code below\n",
        "# How to get a token: https://huggingface.co/docs/hub/en/security-tokens\n",
        "\n",
        "# https://huggingface.co/datasets/MongoDB/embedded_movies\n",
        "dataset = load_dataset(\"MongoDB/embedded_movies\", split=\"train\", streaming=True)\n",
        "dataset = dataset.take(4000)\n",
        "\n",
        "# Convert the dataset to a pandas dataframe\n",
        "dataset_df = pd.DataFrame(dataset)\n",
        "\n",
        "dataset_df.head(5)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "EvHrNR5fJmz1"
      },
      "source": [
        "## Data Cleaning"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 6,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 1000
        },
        "id": "0saXweilXblD",
        "outputId": "970042d9-7ade-4955-c5d1-00ba747d4c74"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "\n",
            "Number of missing values in each column after removal:\n",
            "plot                    0\n",
            "runtime                14\n",
            "genres                  0\n",
            "fullplot                0\n",
            "directors              12\n",
            "writers                13\n",
            "countries               0\n",
            "poster                 78\n",
            "languages               1\n",
            "cast                    1\n",
            "title                   0\n",
            "num_mflix_comments      0\n",
            "rated                 279\n",
            "imdb                    0\n",
            "awards                  0\n",
            "type                    0\n",
            "metacritic            893\n",
            "plot_embedding          1\n",
            "dtype: int64\n"
          ]
        },
        {
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              "      <th>cast</th>\n",
              "      <th>title</th>\n",
              "      <th>num_mflix_comments</th>\n",
              "      <th>rated</th>\n",
              "      <th>imdb</th>\n",
              "      <th>awards</th>\n",
              "      <th>type</th>\n",
              "      <th>metacritic</th>\n",
              "    </tr>\n",
              "  </thead>\n",
              "  <tbody>\n",
              "    <tr>\n",
              "      <th>0</th>\n",
              "      <td>Young Pauline is left a lot of money when her ...</td>\n",
              "      <td>199.0</td>\n",
              "      <td>[Action]</td>\n",
              "      <td>Young Pauline is left a lot of money when her ...</td>\n",
              "      <td>[Louis J. Gasnier, Donald MacKenzie]</td>\n",
              "      <td>[Charles W. Goddard (screenplay), Basil Dickey...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BMzgxOD...</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Pearl White, Crane Wilbur, Paul Panzer, Edwar...</td>\n",
              "      <td>The Perils of Pauline</td>\n",
              "      <td>0</td>\n",
              "      <td>None</td>\n",
              "      <td>{'id': 4465, 'rating': 7.6, 'votes': 744}</td>\n",
              "      <td>{'nominations': 0, 'text': '1 win.', 'wins': 1}</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>1</th>\n",
              "      <td>A penniless young man tries to save an heiress...</td>\n",
              "      <td>22.0</td>\n",
              "      <td>[Comedy, Short, Action]</td>\n",
              "      <td>As a penniless man worries about how he will m...</td>\n",
              "      <td>[Alfred J. Goulding, Hal Roach]</td>\n",
              "      <td>[H.M. Walker (titles)]</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BNzE1OW...</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Harold Lloyd, Mildred Davis, 'Snub' Pollard, ...</td>\n",
              "      <td>From Hand to Mouth</td>\n",
              "      <td>0</td>\n",
              "      <td>TV-G</td>\n",
              "      <td>{'id': 10146, 'rating': 7.0, 'votes': 639}</td>\n",
              "      <td>{'nominations': 1, 'text': '1 nomination.', 'w...</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>2</th>\n",
              "      <td>Michael \"Beau\" Geste leaves England in disgrac...</td>\n",
              "      <td>101.0</td>\n",
              "      <td>[Action, Adventure, Drama]</td>\n",
              "      <td>Michael \"Beau\" Geste leaves England in disgrac...</td>\n",
              "      <td>[Herbert Brenon]</td>\n",
              "      <td>[Herbert Brenon (adaptation), John Russell (ad...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>None</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Ronald Colman, Neil Hamilton, Ralph Forbes, A...</td>\n",
              "      <td>Beau Geste</td>\n",
              "      <td>0</td>\n",
              "      <td>None</td>\n",
              "      <td>{'id': 16634, 'rating': 6.9, 'votes': 222}</td>\n",
              "      <td>{'nominations': 0, 'text': '1 win.', 'wins': 1}</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Seeking revenge, an athletic young man joins t...</td>\n",
              "      <td>88.0</td>\n",
              "      <td>[Adventure, Action]</td>\n",
              "      <td>A nobleman vows to avenge the death of his fat...</td>\n",
              "      <td>[Albert Parker]</td>\n",
              "      <td>[Douglas Fairbanks (story), Jack Cunningham (a...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BMzU0ND...</td>\n",
              "      <td>None</td>\n",
              "      <td>[Billie Dove, Tempe Pigott, Donald Crisp, Sam ...</td>\n",
              "      <td>The Black Pirate</td>\n",
              "      <td>1</td>\n",
              "      <td>None</td>\n",
              "      <td>{'id': 16654, 'rating': 7.2, 'votes': 1146}</td>\n",
              "      <td>{'nominations': 0, 'text': '1 win.', 'wins': 1}</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>An irresponsible young millionaire changes his...</td>\n",
              "      <td>58.0</td>\n",
              "      <td>[Action, Comedy, Romance]</td>\n",
              "      <td>The Uptown Boy, J. Harold Manners (Lloyd) is a...</td>\n",
              "      <td>[Sam Taylor]</td>\n",
              "      <td>[Ted Wilde (story), John Grey (story), Clyde B...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BMTcxMT...</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Harold Lloyd, Jobyna Ralston, Noah Young, Jim...</td>\n",
              "      <td>For Heaven's Sake</td>\n",
              "      <td>0</td>\n",
              "      <td>PASSED</td>\n",
              "      <td>{'id': 16895, 'rating': 7.6, 'votes': 918}</td>\n",
              "      <td>{'nominations': 1, 'text': '1 nomination.', 'w...</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
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              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "    .colab-df-buttons div {\n",
              "      margin-bottom: 4px;\n",
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              "    [theme=dark] .colab-df-convert {\n",
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              "      fill: #D2E3FC;\n",
              "    }\n",
              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
              "      background-color: #434B5C;\n",
              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
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              "      const buttonEl =\n",
              "        document.querySelector('#df-90795e89-efe3-40fd-b2ca-c59de1beb32f button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-90795e89-efe3-40fd-b2ca-c59de1beb32f');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
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              "        element.appendChild(docLink);\n",
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              "\n",
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              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-1347a2a7-ad14-46cb-8e08-f1aa86e8031a')\"\n",
              "            title=\"Suggest charts\"\n",
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              "\n",
              "<svg xmlns=\"http://www.w3.org/2000/svg\" height=\"24px\"viewBox=\"0 0 24 24\"\n",
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              "    <g>\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
              "      --bg-color: #3B4455;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
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              "    }\n",
              "    30% {\n",
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              "      border-left-color: var(--fill-color);\n",
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              "    60% {\n",
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              "    }\n",
              "    80% {\n",
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              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-1347a2a7-ad14-46cb-8e08-f1aa86e8031a button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                                plot  runtime  \\\n",
              "0  Young Pauline is left a lot of money when her ...    199.0   \n",
              "1  A penniless young man tries to save an heiress...     22.0   \n",
              "2  Michael \"Beau\" Geste leaves England in disgrac...    101.0   \n",
              "3  Seeking revenge, an athletic young man joins t...     88.0   \n",
              "4  An irresponsible young millionaire changes his...     58.0   \n",
              "\n",
              "                       genres  \\\n",
              "0                    [Action]   \n",
              "1     [Comedy, Short, Action]   \n",
              "2  [Action, Adventure, Drama]   \n",
              "3         [Adventure, Action]   \n",
              "4   [Action, Comedy, Romance]   \n",
              "\n",
              "                                            fullplot  \\\n",
              "0  Young Pauline is left a lot of money when her ...   \n",
              "1  As a penniless man worries about how he will m...   \n",
              "2  Michael \"Beau\" Geste leaves England in disgrac...   \n",
              "3  A nobleman vows to avenge the death of his fat...   \n",
              "4  The Uptown Boy, J. Harold Manners (Lloyd) is a...   \n",
              "\n",
              "                              directors  \\\n",
              "0  [Louis J. Gasnier, Donald MacKenzie]   \n",
              "1       [Alfred J. Goulding, Hal Roach]   \n",
              "2                      [Herbert Brenon]   \n",
              "3                       [Albert Parker]   \n",
              "4                          [Sam Taylor]   \n",
              "\n",
              "                                             writers countries  \\\n",
              "0  [Charles W. Goddard (screenplay), Basil Dickey...     [USA]   \n",
              "1                             [H.M. Walker (titles)]     [USA]   \n",
              "2  [Herbert Brenon (adaptation), John Russell (ad...     [USA]   \n",
              "3  [Douglas Fairbanks (story), Jack Cunningham (a...     [USA]   \n",
              "4  [Ted Wilde (story), John Grey (story), Clyde B...     [USA]   \n",
              "\n",
              "                                              poster  languages  \\\n",
              "0  https://m.media-amazon.com/images/M/MV5BMzgxOD...  [English]   \n",
              "1  https://m.media-amazon.com/images/M/MV5BNzE1OW...  [English]   \n",
              "2                                               None  [English]   \n",
              "3  https://m.media-amazon.com/images/M/MV5BMzU0ND...       None   \n",
              "4  https://m.media-amazon.com/images/M/MV5BMTcxMT...  [English]   \n",
              "\n",
              "                                                cast                  title  \\\n",
              "0  [Pearl White, Crane Wilbur, Paul Panzer, Edwar...  The Perils of Pauline   \n",
              "1  [Harold Lloyd, Mildred Davis, 'Snub' Pollard, ...     From Hand to Mouth   \n",
              "2  [Ronald Colman, Neil Hamilton, Ralph Forbes, A...             Beau Geste   \n",
              "3  [Billie Dove, Tempe Pigott, Donald Crisp, Sam ...       The Black Pirate   \n",
              "4  [Harold Lloyd, Jobyna Ralston, Noah Young, Jim...      For Heaven's Sake   \n",
              "\n",
              "   num_mflix_comments   rated                                         imdb  \\\n",
              "0                   0    None    {'id': 4465, 'rating': 7.6, 'votes': 744}   \n",
              "1                   0    TV-G   {'id': 10146, 'rating': 7.0, 'votes': 639}   \n",
              "2                   0    None   {'id': 16634, 'rating': 6.9, 'votes': 222}   \n",
              "3                   1    None  {'id': 16654, 'rating': 7.2, 'votes': 1146}   \n",
              "4                   0  PASSED   {'id': 16895, 'rating': 7.6, 'votes': 918}   \n",
              "\n",
              "                                              awards   type  metacritic  \n",
              "0    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN  \n",
              "1  {'nominations': 1, 'text': '1 nomination.', 'w...  movie         NaN  \n",
              "2    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN  \n",
              "3    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN  \n",
              "4  {'nominations': 1, 'text': '1 nomination.', 'w...  movie         NaN  "
            ]
          },
          "execution_count": 6,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Data Preparation\n",
        "\n",
        "# Remove data point where plot coloumn is missing\n",
        "dataset_df = dataset_df.dropna(subset=[\"fullplot\"])\n",
        "print(\"\\nNumber of missing values in each column after removal:\")\n",
        "print(dataset_df.isnull().sum())\n",
        "\n",
        "# Remove the plot_embedding from each data point in the dataset as we are going to create new embeddings with an open source embedding model from Hugging Face\n",
        "dataset_df = dataset_df.drop(columns=[\"plot_embedding\"])\n",
        "dataset_df.head(5)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "iY00KJM_Jn2_"
      },
      "source": [
        "## Embedding Generation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 7,
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        "colab": {
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        {
          "data": {
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              "modules.json:   0%|          | 0.00/385 [00:00<?, ?B/s]"
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              "README.md:   0%|          | 0.00/67.9k [00:00<?, ?B/s]"
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              "vocab.txt:   0%|          | 0.00/232k [00:00<?, ?B/s]"
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              "special_tokens_map.json:   0%|          | 0.00/125 [00:00<?, ?B/s]"
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        {
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            "text/plain": [
              "1_Pooling/config.json:   0%|          | 0.00/191 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
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        },
        {
          "name": "stderr",
          "output_type": "stream",
          "text": [
            "Generating embeddings: 100%|██████████| 1452/1452 [00:36<00:00, 39.52it/s]\n"
          ]
        }
      ],
      "source": [
        "from sentence_transformers import SentenceTransformer\n",
        "from tqdm import tqdm\n",
        "\n",
        "# https://huggingface.co/thenlper/gte-large\n",
        "embedding_model = SentenceTransformer(\"thenlper/gte-large\")\n",
        "\n",
        "\n",
        "def get_embedding(text: str) -> list[float]:\n",
        "    if not text.strip():\n",
        "        print(\"Attempted to get embedding for empty text.\")\n",
        "        return []\n",
        "\n",
        "    embedding = embedding_model.encode(text)\n",
        "\n",
        "    return embedding.tolist()\n",
        "\n",
        "\n",
        "# Apply the embedding function with a progress bar\n",
        "tqdm.pandas(desc=\"Generating embeddings\")\n",
        "dataset_df[\"embedding\"] = dataset_df[\"fullplot\"].progress_apply(get_embedding)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 8,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 747
        },
        "id": "-M4oKALcYuGo",
        "outputId": "d37a26ea-ebc6-41b0-9056-ce1dd9e02f0f"
      },
      "outputs": [
        {
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              "      <th>0</th>\n",
              "      <td>Young Pauline is left a lot of money when her ...</td>\n",
              "      <td>199.0</td>\n",
              "      <td>[Action]</td>\n",
              "      <td>Young Pauline is left a lot of money when her ...</td>\n",
              "      <td>[Louis J. Gasnier, Donald MacKenzie]</td>\n",
              "      <td>[Charles W. Goddard (screenplay), Basil Dickey...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BMzgxOD...</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Pearl White, Crane Wilbur, Paul Panzer, Edwar...</td>\n",
              "      <td>The Perils of Pauline</td>\n",
              "      <td>0</td>\n",
              "      <td>None</td>\n",
              "      <td>{'id': 4465, 'rating': 7.6, 'votes': 744}</td>\n",
              "      <td>{'nominations': 0, 'text': '1 win.', 'wins': 1}</td>\n",
              "      <td>movie</td>\n",
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              "      <td>[-0.009285833686590195, -0.005062105134129524,...</td>\n",
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              "      <th>1</th>\n",
              "      <td>A penniless young man tries to save an heiress...</td>\n",
              "      <td>22.0</td>\n",
              "      <td>[Comedy, Short, Action]</td>\n",
              "      <td>As a penniless man worries about how he will m...</td>\n",
              "      <td>[Alfred J. Goulding, Hal Roach]</td>\n",
              "      <td>[H.M. Walker (titles)]</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BNzE1OW...</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Harold Lloyd, Mildred Davis, 'Snub' Pollard, ...</td>\n",
              "      <td>From Hand to Mouth</td>\n",
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              "      <td>{'id': 10146, 'rating': 7.0, 'votes': 639}</td>\n",
              "      <td>{'nominations': 1, 'text': '1 nomination.', 'w...</td>\n",
              "      <td>movie</td>\n",
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              "      <td>[-0.002439383417367935, 0.02309592068195343, -...</td>\n",
              "    </tr>\n",
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              "      <th>2</th>\n",
              "      <td>Michael \"Beau\" Geste leaves England in disgrac...</td>\n",
              "      <td>101.0</td>\n",
              "      <td>[Action, Adventure, Drama]</td>\n",
              "      <td>Michael \"Beau\" Geste leaves England in disgrac...</td>\n",
              "      <td>[Herbert Brenon]</td>\n",
              "      <td>[Herbert Brenon (adaptation), John Russell (ad...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>None</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Ronald Colman, Neil Hamilton, Ralph Forbes, A...</td>\n",
              "      <td>Beau Geste</td>\n",
              "      <td>0</td>\n",
              "      <td>None</td>\n",
              "      <td>{'id': 16634, 'rating': 6.9, 'votes': 222}</td>\n",
              "      <td>{'nominations': 0, 'text': '1 win.', 'wins': 1}</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[0.012204288505017757, -0.011455747298896313, ...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>3</th>\n",
              "      <td>Seeking revenge, an athletic young man joins t...</td>\n",
              "      <td>88.0</td>\n",
              "      <td>[Adventure, Action]</td>\n",
              "      <td>A nobleman vows to avenge the death of his fat...</td>\n",
              "      <td>[Albert Parker]</td>\n",
              "      <td>[Douglas Fairbanks (story), Jack Cunningham (a...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BMzU0ND...</td>\n",
              "      <td>None</td>\n",
              "      <td>[Billie Dove, Tempe Pigott, Donald Crisp, Sam ...</td>\n",
              "      <td>The Black Pirate</td>\n",
              "      <td>1</td>\n",
              "      <td>None</td>\n",
              "      <td>{'id': 16654, 'rating': 7.2, 'votes': 1146}</td>\n",
              "      <td>{'nominations': 0, 'text': '1 win.', 'wins': 1}</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[0.004541359841823578, -0.0006100474274717271,...</td>\n",
              "    </tr>\n",
              "    <tr>\n",
              "      <th>4</th>\n",
              "      <td>An irresponsible young millionaire changes his...</td>\n",
              "      <td>58.0</td>\n",
              "      <td>[Action, Comedy, Romance]</td>\n",
              "      <td>The Uptown Boy, J. Harold Manners (Lloyd) is a...</td>\n",
              "      <td>[Sam Taylor]</td>\n",
              "      <td>[Ted Wilde (story), John Grey (story), Clyde B...</td>\n",
              "      <td>[USA]</td>\n",
              "      <td>https://m.media-amazon.com/images/M/MV5BMTcxMT...</td>\n",
              "      <td>[English]</td>\n",
              "      <td>[Harold Lloyd, Jobyna Ralston, Noah Young, Jim...</td>\n",
              "      <td>For Heaven's Sake</td>\n",
              "      <td>0</td>\n",
              "      <td>PASSED</td>\n",
              "      <td>{'id': 16895, 'rating': 7.6, 'votes': 918}</td>\n",
              "      <td>{'nominations': 1, 'text': '1 nomination.', 'w...</td>\n",
              "      <td>movie</td>\n",
              "      <td>NaN</td>\n",
              "      <td>[-0.002225597621873021, 0.011567803099751472, ...</td>\n",
              "    </tr>\n",
              "  </tbody>\n",
              "</table>\n",
              "</div>\n",
              "    <div class=\"colab-df-buttons\">\n",
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              "  <style>\n",
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              "\n",
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              "      width: 32px;\n",
              "    }\n",
              "\n",
              "    .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 2px rgba(60, 64, 67, 0.3), 0px 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
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              "\n",
              "    .colab-df-buttons div {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert {\n",
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              "\n",
              "    [theme=dark] .colab-df-convert:hover {\n",
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              "      box-shadow: 0px 1px 3px 1px rgba(0, 0, 0, 0.15);\n",
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              "      fill: #FFFFFF;\n",
              "    }\n",
              "  </style>\n",
              "\n",
              "    <script>\n",
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              "        document.querySelector('#df-f9f46056-f6b0-46e1-bb5e-d3c6ce6f243b button.colab-df-convert');\n",
              "      buttonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "\n",
              "      async function convertToInteractive(key) {\n",
              "        const element = document.querySelector('#df-f9f46056-f6b0-46e1-bb5e-d3c6ce6f243b');\n",
              "        const dataTable =\n",
              "          await google.colab.kernel.invokeFunction('convertToInteractive',\n",
              "                                                    [key], {});\n",
              "        if (!dataTable) return;\n",
              "\n",
              "        const docLinkHtml = 'Like what you see? Visit the ' +\n",
              "          '<a target=\"_blank\" href=https://colab.research.google.com/notebooks/data_table.ipynb>data table notebook</a>'\n",
              "          + ' to learn more about interactive tables.';\n",
              "        element.innerHTML = '';\n",
              "        dataTable['output_type'] = 'display_data';\n",
              "        await google.colab.output.renderOutput(dataTable, element);\n",
              "        const docLink = document.createElement('div');\n",
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              "        element.appendChild(docLink);\n",
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              "\n",
              "\n",
              "<div id=\"df-d64d441a-5b76-45df-a5c6-1004fb0b77da\">\n",
              "  <button class=\"colab-df-quickchart\" onclick=\"quickchart('df-d64d441a-5b76-45df-a5c6-1004fb0b77da')\"\n",
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              "\n",
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              "    </g>\n",
              "</svg>\n",
              "  </button>\n",
              "\n",
              "<style>\n",
              "  .colab-df-quickchart {\n",
              "      --bg-color: #E8F0FE;\n",
              "      --fill-color: #1967D2;\n",
              "      --hover-bg-color: #E2EBFA;\n",
              "      --hover-fill-color: #174EA6;\n",
              "      --disabled-fill-color: #AAA;\n",
              "      --disabled-bg-color: #DDD;\n",
              "  }\n",
              "\n",
              "  [theme=dark] .colab-df-quickchart {\n",
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              "      --fill-color: #D2E3FC;\n",
              "      --hover-bg-color: #434B5C;\n",
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              "      --disabled-bg-color: #3B4455;\n",
              "      --disabled-fill-color: #666;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart {\n",
              "    background-color: var(--bg-color);\n",
              "    border: none;\n",
              "    border-radius: 50%;\n",
              "    cursor: pointer;\n",
              "    display: none;\n",
              "    fill: var(--fill-color);\n",
              "    height: 32px;\n",
              "    padding: 0;\n",
              "    width: 32px;\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart:hover {\n",
              "    background-color: var(--hover-bg-color);\n",
              "    box-shadow: 0 1px 2px rgba(60, 64, 67, 0.3), 0 1px 3px 1px rgba(60, 64, 67, 0.15);\n",
              "    fill: var(--button-hover-fill-color);\n",
              "  }\n",
              "\n",
              "  .colab-df-quickchart-complete:disabled,\n",
              "  .colab-df-quickchart-complete:disabled:hover {\n",
              "    background-color: var(--disabled-bg-color);\n",
              "    fill: var(--disabled-fill-color);\n",
              "    box-shadow: none;\n",
              "  }\n",
              "\n",
              "  .colab-df-spinner {\n",
              "    border: 2px solid var(--fill-color);\n",
              "    border-color: transparent;\n",
              "    border-bottom-color: var(--fill-color);\n",
              "    animation:\n",
              "      spin 1s steps(1) infinite;\n",
              "  }\n",
              "\n",
              "  @keyframes spin {\n",
              "    0% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "      border-left-color: var(--fill-color);\n",
              "    }\n",
              "    20% {\n",
              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
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              "      border-color: transparent;\n",
              "      border-left-color: var(--fill-color);\n",
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              "    }\n",
              "    60% {\n",
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              "    }\n",
              "    80% {\n",
              "      border-color: transparent;\n",
              "      border-right-color: var(--fill-color);\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "    90% {\n",
              "      border-color: transparent;\n",
              "      border-bottom-color: var(--fill-color);\n",
              "    }\n",
              "  }\n",
              "</style>\n",
              "\n",
              "  <script>\n",
              "    async function quickchart(key) {\n",
              "      const quickchartButtonEl =\n",
              "        document.querySelector('#' + key + ' button');\n",
              "      quickchartButtonEl.disabled = true;  // To prevent multiple clicks.\n",
              "      quickchartButtonEl.classList.add('colab-df-spinner');\n",
              "      try {\n",
              "        const charts = await google.colab.kernel.invokeFunction(\n",
              "            'suggestCharts', [key], {});\n",
              "      } catch (error) {\n",
              "        console.error('Error during call to suggestCharts:', error);\n",
              "      }\n",
              "      quickchartButtonEl.classList.remove('colab-df-spinner');\n",
              "      quickchartButtonEl.classList.add('colab-df-quickchart-complete');\n",
              "    }\n",
              "    (() => {\n",
              "      let quickchartButtonEl =\n",
              "        document.querySelector('#df-d64d441a-5b76-45df-a5c6-1004fb0b77da button');\n",
              "      quickchartButtonEl.style.display =\n",
              "        google.colab.kernel.accessAllowed ? 'block' : 'none';\n",
              "    })();\n",
              "  </script>\n",
              "</div>\n",
              "\n",
              "    </div>\n",
              "  </div>\n"
            ],
            "text/plain": [
              "                                                plot  runtime  \\\n",
              "0  Young Pauline is left a lot of money when her ...    199.0   \n",
              "1  A penniless young man tries to save an heiress...     22.0   \n",
              "2  Michael \"Beau\" Geste leaves England in disgrac...    101.0   \n",
              "3  Seeking revenge, an athletic young man joins t...     88.0   \n",
              "4  An irresponsible young millionaire changes his...     58.0   \n",
              "\n",
              "                       genres  \\\n",
              "0                    [Action]   \n",
              "1     [Comedy, Short, Action]   \n",
              "2  [Action, Adventure, Drama]   \n",
              "3         [Adventure, Action]   \n",
              "4   [Action, Comedy, Romance]   \n",
              "\n",
              "                                            fullplot  \\\n",
              "0  Young Pauline is left a lot of money when her ...   \n",
              "1  As a penniless man worries about how he will m...   \n",
              "2  Michael \"Beau\" Geste leaves England in disgrac...   \n",
              "3  A nobleman vows to avenge the death of his fat...   \n",
              "4  The Uptown Boy, J. Harold Manners (Lloyd) is a...   \n",
              "\n",
              "                              directors  \\\n",
              "0  [Louis J. Gasnier, Donald MacKenzie]   \n",
              "1       [Alfred J. Goulding, Hal Roach]   \n",
              "2                      [Herbert Brenon]   \n",
              "3                       [Albert Parker]   \n",
              "4                          [Sam Taylor]   \n",
              "\n",
              "                                             writers countries  \\\n",
              "0  [Charles W. Goddard (screenplay), Basil Dickey...     [USA]   \n",
              "1                             [H.M. Walker (titles)]     [USA]   \n",
              "2  [Herbert Brenon (adaptation), John Russell (ad...     [USA]   \n",
              "3  [Douglas Fairbanks (story), Jack Cunningham (a...     [USA]   \n",
              "4  [Ted Wilde (story), John Grey (story), Clyde B...     [USA]   \n",
              "\n",
              "                                              poster  languages  \\\n",
              "0  https://m.media-amazon.com/images/M/MV5BMzgxOD...  [English]   \n",
              "1  https://m.media-amazon.com/images/M/MV5BNzE1OW...  [English]   \n",
              "2                                               None  [English]   \n",
              "3  https://m.media-amazon.com/images/M/MV5BMzU0ND...       None   \n",
              "4  https://m.media-amazon.com/images/M/MV5BMTcxMT...  [English]   \n",
              "\n",
              "                                                cast                  title  \\\n",
              "0  [Pearl White, Crane Wilbur, Paul Panzer, Edwar...  The Perils of Pauline   \n",
              "1  [Harold Lloyd, Mildred Davis, 'Snub' Pollard, ...     From Hand to Mouth   \n",
              "2  [Ronald Colman, Neil Hamilton, Ralph Forbes, A...             Beau Geste   \n",
              "3  [Billie Dove, Tempe Pigott, Donald Crisp, Sam ...       The Black Pirate   \n",
              "4  [Harold Lloyd, Jobyna Ralston, Noah Young, Jim...      For Heaven's Sake   \n",
              "\n",
              "   num_mflix_comments   rated                                         imdb  \\\n",
              "0                   0    None    {'id': 4465, 'rating': 7.6, 'votes': 744}   \n",
              "1                   0    TV-G   {'id': 10146, 'rating': 7.0, 'votes': 639}   \n",
              "2                   0    None   {'id': 16634, 'rating': 6.9, 'votes': 222}   \n",
              "3                   1    None  {'id': 16654, 'rating': 7.2, 'votes': 1146}   \n",
              "4                   0  PASSED   {'id': 16895, 'rating': 7.6, 'votes': 918}   \n",
              "\n",
              "                                              awards   type  metacritic  \\\n",
              "0    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN   \n",
              "1  {'nominations': 1, 'text': '1 nomination.', 'w...  movie         NaN   \n",
              "2    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN   \n",
              "3    {'nominations': 0, 'text': '1 win.', 'wins': 1}  movie         NaN   \n",
              "4  {'nominations': 1, 'text': '1 nomination.', 'w...  movie         NaN   \n",
              "\n",
              "                                           embedding  \n",
              "0  [-0.009285833686590195, -0.005062105134129524,...  \n",
              "1  [-0.002439383417367935, 0.02309592068195343, -...  \n",
              "2  [0.012204288505017757, -0.011455747298896313, ...  \n",
              "3  [0.004541359841823578, -0.0006100474274717271,...  \n",
              "4  [-0.002225597621873021, 0.011567803099751472, ...  "
            ]
          },
          "execution_count": 8,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "dataset_df.head()"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "M-y3pyy6K42N"
      },
      "source": [
        "## MongoDB Vector Database and Connection Setup"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "t71kFjCsJ3ad"
      },
      "source": [
        "\n",
        "MongoDB acts as both an operational and a vector database for the RAG system.\n",
        "MongoDB Atlas specifically provides a database solution that efficiently stores, queries and retrieves vector embeddings.\n",
        "\n",
        "Creating a database and collection within MongoDB is made simple with MongoDB Atlas.\n",
        "\n",
        "1. First, register for a [MongoDB Atlas account](https://www.mongodb.com/cloud/atlas/register). For existing users, sign into MongoDB Atlas.\n",
        "2. [Follow the instructions](https://www.mongodb.com/docs/atlas/tutorial/deploy-free-tier-cluster/). Select Atlas UI as the procedure to deploy your first cluster.\n",
        "3. Create the database: `movie_rec_sys`.\n",
        "4. Within the database ` movie_collection`, create the collection ‘listings_reviews’.\n",
        "5. Create a [vector search index](https://www.mongodb.com/docs/atlas/atlas-vector-search/create-index/#procedure/) named vector_index for the ‘listings_reviews’ collection. This index enables the RAG application to retrieve records as additional context to supplement user queries via vector search. Below is the JSON definition of the data collection vector search index.\n",
        "\n",
        "Your vector search index created on MongoDB Atlas should look like below:\n",
        "\n",
        "```\n",
        "{\n",
        "  \"fields\": [\n",
        "    {\n",
        "      \"numDimensions\": 1024,\n",
        "      \"path\": \"embedding\",\n",
        "      \"similarity\": \"cosine\",\n",
        "      \"type\": \"vector\"\n",
        "    }\n",
        "  ]\n",
        "}\n",
        "\n",
        "```\n",
        "\n",
        "Follow MongoDB’s [steps to get the connection](https://www.mongodb.com/docs/manual/reference/connection-string/) string from the Atlas UI. After setting up the database and obtaining the Atlas cluster connection URI, securely store the URI within your development environment."
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 13,
      "metadata": {
        "id": "LAwrsIXPKfPt"
      },
      "outputs": [],
      "source": [
        "import os\n",
        "\n",
        "os.environ[\"MONGO_URI\"] = \"\""
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 18,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "BEG4BtKWXefx",
        "outputId": "99dcc1fc-38d5-47d7-c1c2-3613b0b9a2e3"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Connection to MongoDB successful\n"
          ]
        }
      ],
      "source": [
        "import pymongo\n",
        "\n",
        "\n",
        "def get_mongo_client(mongo_uri):\n",
        "    \"\"\"Establish and validate connection to the MongoDB.\"\"\"\n",
        "\n",
        "    client = pymongo.MongoClient(mongo_uri, appname=\"devrel.showcase.gemma2.python\")\n",
        "\n",
        "    # Validate the connection\n",
        "    ping_result = client.admin.command(\"ping\")\n",
        "    if ping_result.get(\"ok\") == 1.0:\n",
        "        # Connection successful\n",
        "        print(\"Connection to MongoDB successful\")\n",
        "        return client\n",
        "    print(\"Connection to MongoDB failed\")\n",
        "    return None\n",
        "\n",
        "\n",
        "mongo_uri = os.environ[\"MONGO_URI\"]\n",
        "\n",
        "if not mongo_uri:\n",
        "    print(\"MONGO_URI not set in environment variables\")\n",
        "\n",
        "mongo_client = get_mongo_client(mongo_uri)\n",
        "\n",
        "DB_NAME = \"movie_rec_sys\"\n",
        "COLLECTION_NAME = \"movie_collection\"\n",
        "\n",
        "db = mongo_client.get_database(DB_NAME)\n",
        "collection = db.get_collection(COLLECTION_NAME)"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 19,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "5wV9TkDrXhZA",
        "outputId": "7e6a4b4e-283d-414e-c0eb-3f36b852afc3"
      },
      "outputs": [
        {
          "data": {
            "text/plain": [
              "DeleteResult({'n': 0, 'electionId': ObjectId('7fffffff000000000000002a'), 'opTime': {'ts': Timestamp(1719600641, 43), 't': 42}, 'ok': 1.0, '$clusterTime': {'clusterTime': Timestamp(1719600641, 43), 'signature': {'hash': b'\\tS\\xb0Ja\\xd5\\x90\\xf6\\xed`\\xef>\\x94\\xab\\x05\\xd2[\\xdbM\\xc1', 'keyId': 7320226449804230662}}, 'operationTime': Timestamp(1719600641, 43)}, acknowledged=True)"
            ]
          },
          "execution_count": 19,
          "metadata": {},
          "output_type": "execute_result"
        }
      ],
      "source": [
        "# Delete any existing records in the collection\n",
        "collection.delete_many({})"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "dvvlzve5K9zf"
      },
      "source": [
        "## Data Ingestion"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 20,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "F4obMlpzXkpL",
        "outputId": "5ef779a8-27f0-48f7-d91b-a29eba065a7b"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Data ingestion into MongoDB completed\n"
          ]
        }
      ],
      "source": [
        "documents = dataset_df.to_dict(\"records\")\n",
        "collection.insert_many(documents)\n",
        "\n",
        "print(\"Data ingestion into MongoDB completed\")"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "8b_UwtFoLB-2"
      },
      "source": [
        "## Vector Search Operation"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 21,
      "metadata": {
        "id": "3GOkbnqtXns_"
      },
      "outputs": [],
      "source": [
        "def vector_search(user_query, collection):\n",
        "    \"\"\"\n",
        "    Perform a vector search in the MongoDB collection based on the user query.\n",
        "\n",
        "    Args:\n",
        "    user_query (str): The user's query string.\n",
        "    collection (MongoCollection): The MongoDB collection to search.\n",
        "\n",
        "    Returns:\n",
        "    list: A list of matching documents.\n",
        "    \"\"\"\n",
        "\n",
        "    # Generate embedding for the user query\n",
        "    query_embedding = get_embedding(user_query)\n",
        "\n",
        "    if query_embedding is None:\n",
        "        return \"Invalid query or embedding generation failed.\"\n",
        "\n",
        "    # Define the vector search pipeline\n",
        "    vector_search_stage = {\n",
        "        \"$vectorSearch\": {\n",
        "            \"index\": \"vector_index\",\n",
        "            \"queryVector\": query_embedding,\n",
        "            \"path\": \"embedding\",\n",
        "            \"numCandidates\": 150,  # Number of candidate matches to consider\n",
        "            \"limit\": 4,  # Return top 4 matches\n",
        "        }\n",
        "    }\n",
        "\n",
        "    unset_stage = {\n",
        "        \"$unset\": \"embedding\"  # Exclude the 'embedding' field from the results\n",
        "    }\n",
        "\n",
        "    project_stage = {\n",
        "        \"$project\": {\n",
        "            \"_id\": 0,  # Exclude the _id field\n",
        "            \"fullplot\": 1,  # Include the plot field\n",
        "            \"title\": 1,  # Include the title field\n",
        "            \"genres\": 1,  # Include the genres field\n",
        "            \"score\": {\n",
        "                \"$meta\": \"vectorSearchScore\"  # Include the search score\n",
        "            },\n",
        "        }\n",
        "    }\n",
        "\n",
        "    pipeline = [vector_search_stage, unset_stage, project_stage]\n",
        "\n",
        "    # Execute the search\n",
        "    results = collection.aggregate(pipeline)\n",
        "    return list(results)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "NF-A-0zELFX9"
      },
      "source": [
        "## Handle User Results"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 22,
      "metadata": {
        "id": "7fGN2kK2Xsd1"
      },
      "outputs": [],
      "source": [
        "def get_search_result(query, collection):\n",
        "    get_knowledge = vector_search(query, collection)\n",
        "\n",
        "    search_result = \"\"\n",
        "    for result in get_knowledge:\n",
        "        search_result += f\"Title: {result.get('title', 'N/A')}, Plot: {result.get('fullplot', 'N/A')}\\n\"\n",
        "\n",
        "    return search_result"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 23,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "3ETL8LyEXtfc",
        "outputId": "3345ac90-e55e-42b3-e0d8-97d957c4f0e1"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "Query: What is the best romantic movie to watch and why?\n",
            "Continue to answer the query by using the Search Results:\n",
            "Title: Shut Up and Kiss Me!, Plot: Ryan and Pete are 27-year old best friends in Miami, born on the same day and each searching for the perfect woman. Ryan is a rookie stockbroker living with his psychic Mom. Pete is a slick surfer dude yet to find commitment. Each meets the women of their dreams on the same day. Ryan knocks heads in an elevator with the gorgeous Jessica, passing out before getting her number. Pete falls for the insatiable Tiara, but Tiara's uncle is mob boss Vincent Bublione, charged with her protection. This high-energy romantic comedy asks to what extent will you go for true love?\n",
            "Title: Pearl Harbor, Plot: Pearl Harbor is a classic tale of romance set during a war that complicates everything. It all starts when childhood friends Rafe and Danny become Army Air Corps pilots and meet Evelyn, a Navy nurse. Rafe falls head over heels and next thing you know Evelyn and Rafe are hooking up. Then Rafe volunteers to go fight in Britain and Evelyn and Danny get transferred to Pearl Harbor. While Rafe is off fighting everything gets completely whack and next thing you know everybody is in the middle of an air raid we now know as \"Pearl Harbor.\"\n",
            "Title: Titanic, Plot: The plot focuses on the romances of two couples upon the doomed ship's maiden voyage. Isabella Paradine (Catherine Zeta-Jones) is a wealthy woman mourning the loss of her aunt, who reignites a romance with former flame Wynn Park (Peter Gallagher). Meanwhile, a charming ne'er-do-well named Jamie Perse (Mike Doyle) steals a ticket for the ship, and falls for a sweet innocent Irish girl on board. But their romance is threatened by the villainous Simon Doonan (Tim Curry), who has discovered about the ticket and makes Jamie his unwilling accomplice, as well as having sinister plans for the girl.\n",
            "Title: China Girl, Plot: A modern day Romeo & Juliet story is told in New York when an Italian boy and a Chinese girl become lovers, causing a tragic conflict between ethnic gangs.\n",
            ".\n"
          ]
        }
      ],
      "source": [
        "# Conduct query with retrival of sources\n",
        "query = \"What is the best romantic movie to watch and why?\"\n",
        "source_information = get_search_result(query, collection)\n",
        "combined_information = f\"Query: {query}\\nContinue to answer the query by using the Search Results:\\n{source_information}.\"\n",
        "\n",
        "print(combined_information)"
      ]
    },
    {
      "cell_type": "markdown",
      "metadata": {
        "id": "TfsakemuLO-I"
      },
      "source": [
        "## Load Gemma 2"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 24,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/",
          "height": 433,
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          ]
        },
        "id": "nMZSSYH1XwbV",
        "outputId": "b4553418-065a-4e08-d85f-624ab9637540"
      },
      "outputs": [
        {
          "data": {
            "application/vnd.jupyter.widget-view+json": {
              "model_id": "f067e230df4b4fb4b43f37283308f24a",
              "version_major": 2,
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            "text/plain": [
              "tokenizer_config.json:   0%|          | 0.00/40.6k [00:00<?, ?B/s]"
            ]
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          "metadata": {},
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        },
        {
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            "text/plain": [
              "tokenizer.model:   0%|          | 0.00/4.24M [00:00<?, ?B/s]"
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              "config.json:   0%|          | 0.00/857 [00:00<?, ?B/s]"
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              "version_minor": 0
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            "text/plain": [
              "Downloading shards:   0%|          | 0/4 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
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            "text/plain": [
              "model-00001-of-00004.safetensors:   0%|          | 0.00/4.90G [00:00<?, ?B/s]"
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        {
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              "model-00002-of-00004.safetensors:   0%|          | 0.00/4.95G [00:00<?, ?B/s]"
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        {
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            "text/plain": [
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        {
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            "text/plain": [
              "model-00004-of-00004.safetensors:   0%|          | 0.00/3.67G [00:00<?, ?B/s]"
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          },
          "metadata": {},
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        {
          "data": {
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              "version_minor": 0
            },
            "text/plain": [
              "Loading checkpoint shards:   0%|          | 0/4 [00:00<?, ?it/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        },
        {
          "data": {
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              "version_minor": 0
            },
            "text/plain": [
              "generation_config.json:   0%|          | 0.00/173 [00:00<?, ?B/s]"
            ]
          },
          "metadata": {},
          "output_type": "display_data"
        }
      ],
      "source": [
        "import torch\n",
        "from transformers import AutoModelForCausalLM, AutoTokenizer\n",
        "\n",
        "tokenizer = AutoTokenizer.from_pretrained(\"google/gemma-2-9b-it\")\n",
        "model = AutoModelForCausalLM.from_pretrained(\n",
        "    \"google/gemma-2-9b-it\", device_map=\"auto\", torch_dtype=torch.bfloat16\n",
        ")"
      ]
    },
    {
      "cell_type": "code",
      "execution_count": 25,
      "metadata": {
        "colab": {
          "base_uri": "https://localhost:8080/"
        },
        "id": "pUt4aVm5XzUv",
        "outputId": "54d4cba7-f9d6-4c5b-d84f-ee775d558437"
      },
      "outputs": [
        {
          "name": "stdout",
          "output_type": "stream",
          "text": [
            "<bos>Query: What is the best romantic movie to watch and why?\n",
            "Continue to answer the query by using the Search Results:\n",
            "Title: Shut Up and Kiss Me!, Plot: Ryan and Pete are 27-year old best friends in Miami, born on the same day and each searching for the perfect woman. Ryan is a rookie stockbroker living with his psychic Mom. Pete is a slick surfer dude yet to find commitment. Each meets the women of their dreams on the same day. Ryan knocks heads in an elevator with the gorgeous Jessica, passing out before getting her number. Pete falls for the insatiable Tiara, but Tiara's uncle is mob boss Vincent Bublione, charged with her protection. This high-energy romantic comedy asks to what extent will you go for true love?\n",
            "Title: Pearl Harbor, Plot: Pearl Harbor is a classic tale of romance set during a war that complicates everything. It all starts when childhood friends Rafe and Danny become Army Air Corps pilots and meet Evelyn, a Navy nurse. Rafe falls head over heels and next thing you know Evelyn and Rafe are hooking up. Then Rafe volunteers to go fight in Britain and Evelyn and Danny get transferred to Pearl Harbor. While Rafe is off fighting everything gets completely whack and next thing you know everybody is in the middle of an air raid we now know as \"Pearl Harbor.\"\n",
            "Title: Titanic, Plot: The plot focuses on the romances of two couples upon the doomed ship's maiden voyage. Isabella Paradine (Catherine Zeta-Jones) is a wealthy woman mourning the loss of her aunt, who reignites a romance with former flame Wynn Park (Peter Gallagher). Meanwhile, a charming ne'er-do-well named Jamie Perse (Mike Doyle) steals a ticket for the ship, and falls for a sweet innocent Irish girl on board. But their romance is threatened by the villainous Simon Doonan (Tim Curry), who has discovered about the ticket and makes Jamie his unwilling accomplice, as well as having sinister plans for the girl.\n",
            "Title: China Girl, Plot: A modern day Romeo & Juliet story is told in New York when an Italian boy and a Chinese girl become lovers, causing a tragic conflict between ethnic gangs.\n",
            ".\n",
            "\n",
            "Based on the provided movie plots, which one would you recommend as the best romantic movie and why?\n",
            "\n",
            "I would recommend **Shut Up and Kiss Me!** as the best romantic movie from this list. Here's\n"
          ]
        }
      ],
      "source": [
        "input_ids = tokenizer(combined_information, return_tensors=\"pt\").to(\"cuda\")\n",
        "outputs = model.generate(**input_ids, max_length=500)\n",
        "print(tokenizer.decode(outputs[0]))"
      ]
    }
  ],
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